Value-based Communication During COVID-19 Pandemic - A Study on The Twitter Messages of Turkish Ministry of Health

Özet

Influencing the whole world by obliging people to change their daily practices along with their relations and assume different life styles, Covid-19 has brought about some likely deleterious effects in Turkey as well. Undoubtedly, it has caused disturbance and even panic in social and psychological sense. In such cases of uncertainty and panic, communication with the public should be clear, explicit, alleviating and to some extent, guiding. People can be guided and convinced more easily if the level of distress and uncertainty decreases. Such a way of governing and compelling communication consists of different directions, requirements and combined effort. If co-operation is appropriately based on values, this process will be much easier. To that end, public discourse during the outbreak of the pandemic in 2019 was as successful as it was based on the daily life and language of society. Noteworthy, there are similarities between value-based collaboration and governmentality. Policies, customs, patterns and guidelines help maintain control and guidance over collaboration. At this point cooperation acts as a matter of participating in language games that build social and organisational realities that are created, debated, distributed and changed by means of mutual action and cooperation. The purpose of this study is to analyse the messages sent by the Ministry of Health during the pandemic in Turkey via social media, particularly Twitter, in order to find out to which extent these messages encompass the features of value-based communication. Thus, discourse analysis and descriptive research model are going to be implemented together. More specifically, the first tweet in which Corona was first referred was sent on January 25, 2020 and from then on 505 Tweets were posted. For the discourse analysis, 100 tweets that have received the most interaction are going to be used. As for the other descriptive analyses; on the other hand, all 505 tweets are going to be utilized in cluster analysis.